FIELD
[0001] The invention relates to the field of electronic device technologies, and more particularly
to a method for application processing, a storage medium, and an electronic device.
BACKGROUND
[0002] Presently, with the rapid development of terminal technologies, such as smart phones
are getting deeper into people's lives, a variety of applications may be installed
in the smart phones, such as a photo capturing application, a game application, and
a map application, for a user to use.
[0003] However, as functions of the applications become more and more powerful, a storage
space occupied by each application is also increasing, which may affect a normal operation
of a smart phone system.
CN 107 544 898 A discloses a data acquisition method and device, equipment and a storage medium. The
method is applied to the terminal equipment and includes the steps that according
to the use frequency and the use time of every application program, at least one first
application program is acquired, wherein the at least one first application program
is the application program with the highest use frequency and/or the use time closest
to the current time of a user; running data of the at least one first application
program is acquired; the running data corresponding to the at least one first application
program is stored in a running memory of the terminal equipment. According to the
use history of the application program, an application program likely to be used by
the user is predicted, and relative running data is downloaded and cached in the memory
in advance, which makes it unnecessary to download the running data from a network
after the application program is started by the user, so that loading time is saved,
and the problem is avoided that the application program cannot be used due to the
poor network.
CN 107 451 694 A discloses an application prediction method used for context awareness and adaptation
in a mobile system. The application prediction method comprises the following steps
that step 1, record information effective for improving the mobile application prediction
accuracy is extracted from a large amount of data collected by mobile equipment to
act as a training set; step 2, the training set extracted based on the step 1 is trained
by using an unbalanced Bayesian model, and an application use probability model is
obtained through training; and step 3, the application to be used is predicted by
applying the use probability model based on the awared current context information,
the predicted application to be used and the actually used application are compared
to obtain the current prediction accuracy, and then the size of each prediction period
is adaptively adjusted according to the current prediction accuracy by using a flexible
algorithm so as to reduce the training cost. The technical effects of the application
prediction method are that the application prediction accuracy can be enhanced and
the training cost of the prediction model can be effectively reduced.
US 2016/170575 A1 provides an application activation method and apparatus and electronic equipment.
The activation method includes: determining one or more recommended application(s)
according to information on practice of use of applications; and activating the one
or more recommended application(s). With the embodiments of the present invention,
many applications expected to be used need not to be looked for, thereby reducing
a large quantity of repeated operations, and obtaining better user experience.
SUMMARY
[0004] The invention is defined in the independent claims. Preferred embodiments are defined
in dependent claims.
BRIEF DESCRIPTION OF THE DRAWINGS
[0005] In order to clearly illustrate technical solutions in embodiments of the disclosure,
a brief description will be made below to accompanying drawings that need to be used
in the embodiments. Obviously, the accompanying drawings in the following descriptions
are only some embodiments of the disclosure, and for those skilled in the art, other
accompanying drawings can be obtained according to these accompanying drawings without
creative labor.
FIG. 1 is a schematic diagram illustrating a scenario of a method for application
processing according to embodiments of the disclosure.
FIG. 2 is a flow chart illustrating a method for application processing according
to embodiments of the disclosure.
FIG. 3 is a schematic diagram illustrating a scenario for obtaining a target application
according to embodiments of the disclosure.
FIG. 4 is a schematic diagram illustrating a scenario for obtaining a target application
and an alternative application according to embodiments of the disclosure.
FIG. 5 is a schematic diagram illustrating a scenario where a user triggers a target
application according to embodiments of the disclosure.
FIG. 6 is another flow chart illustrating a method for application processing according
to embodiments of the disclosure.
FIG. 7 is a block diagram illustrating an apparatus for application processing according
to embodiments of the disclosure.
FIG. 8 is another block diagram illustrating an apparatus for application processing
according to embodiments of the disclosure.
FIG. 9 is a block diagram illustrating an electronic device according to embodiments
of the disclosure.
FIG. 10 is another block diagram illustrating an electronic device according to embodiments
of the disclosure.
DETAILED DESCRIPTION
[0006] Referring to the accompanying drawings, same reference numerals refer to same elements.
The principle of the disclosure is illustrated by an implementation in a suitable
computing scenario. The following description is based on the illustrated detailed
embodiments of the disclosure.
[0007] Embodiments of the disclosure provide a method for application processing, which
is applied to an electronic device. The method includes: obtaining historical operation
information of the electronic device; obtaining triggering probability values of a
plurality of applications in an application platform installed in the electronic device
based on the historical operation information; selecting an application with a triggering
probability value greater than a first preset probability value as a target application;
downloading resource files of the target application; buffering the resource files
into a storage area corresponding to the application platform; and loading the resource
files stored in the storage area, corresponding to the target application, in response
to detecting a triggering operation on the target application.
[0008] Obtaining the historical operation information of the electronic device, and obtaining
the triggering probability values of the plurality of applications in the application
platform installed in the electronic device based on the historical operation information
may include: obtaining a triggering time point in response to detecting a triggering
operation on the application platform; obtaining historical operation information
of the electronic device in a preset period prior to the triggering time point; and
inputting the historical operation information into a prediction model, the prediction
model for predicting the triggering probability values of the plurality of applications
in the application platform based on the historical operation information.
[0009] Inputting the historical operation information into the prediction model may include:
classifying the historical operation information to obtain first-type information
belonging to user interaction information and second-type information belonging to
system information of the electronic device; increasing a weight of the first-type
information and decreasing a weight of the second-type information; and inputting
the first-type information with the increased weight and the second-type information
with the decreased weight into the prediction model.
[0010] The prediction model includes at least one of: a convolutional neural network model
and a recurrent neural network model.
[0011] Downloading the resource files of the target application may include: obtaining a
data amount of resource files that need to be downloaded for the target application;
determining whether a triggering probability value of the target application is greater
than a second preset probability value under a case that the data amount is greater
than a preset data amount, the second preset probability value being greater than
the first preset probability value; downloading all the resource files of the target
application under a case that the triggering probability value of the target application
is greater than the second preset probability value; and downloading part of the resource
files of the target application under a case that the triggering probability value
of the target application is not greater than the second preset probability value.
[0012] The method may further include: adding an execution entrance of the target application
to a main interface of the electronic device under the case that the triggering probability
value of the target application is greater than the second preset probability value.
[0013] Downloading the resource files of the target application may include: obtaining a
pre-storage capacity corresponding to the target application based on the triggering
probability value of the target application; obtaining a data amount of resource files
that need to be downloaded for the target application; detecting whether the storage
area has a residual capacity under a case that the data amount exceeds the pre-storage
capacity; determining whether the data amount exceeds a sum of the pre-storage capacity
and the residual capacity under a case that there is the residual capacity; and downloading
the resource files of the target application under a case that the data amount does
not exceed the sum of the pre-storage capacity and the residual capacity.
[0014] The method may further include: selecting an application with a triggering probability
value not greater than the first preset probability value but greater than a third
preset probability value as an alternative application, in which the third preset
probability value is smaller than the first preset probability value; adding an execution
entrance of the target application to a first preset position of a main interface
of the application platform; and adding an execution entrance of the alternative application
to a second preset position of the main interface of the application platform.
[0015] There are a plurality of target applications and a plurality of alternative applications.
The second preset position is set around the first preset position.
[0016] There are a plurality of target applications and a plurality of alternative applications.
The plurality of target applications and the plurality of alternative applications
are displayed in an arrangement of the triggering probability values.
[0017] The method also includes: obtaining a new triggering probability value of the target
application under a case that the storage area is full; and deleting the resource
files of the target application under a case that the new triggering probability value
is smaller than the first preset probability value.
[0018] The method also includes: generating and displaying a native interface of the target
application based on a configuration file of the target application included in the
resource files.
[0019] The configuration file includes statements describing the native interface of the
target application. The statements include data required for displaying the native
interface and an operation logic of the native interface.
[0020] Embodiments of the disclosure also provide a storage medium having a computer program
stored thereon. An electronic device is caused to execute the method for application
processing according to any one embodiment described above when the computer program
is operating in the electronic device.
[0021] Embodiments of the disclosure also provide an electronic device. The electronic device
includes a processor and a memory. The memory has a computer program stored thereon.
The processor is coupled to the memory. The processor, by calling the computer program,
is configured to execute: obtain historical operation information of the electronic
device; obtain triggering probability values of a plurality of applications in an
application platform installed in the electronic device based on the historical operation
information; select an application with a triggering probability value greater than
a first preset probability value as a target application; download resource files
of the target application; buffer the resource files into a storage area corresponding
to the application platform; and load the resource files stored in the storage area
and corresponding to the target application, in response to detecting a triggering
operation on the target application.
[0022] During obtaining the historical operation information of the electronic device, and
obtaining the triggering probability values of the plurality of applications in the
application platform based on the historical operation information, the processor
is also configured to: obtain a triggering time point in response to detecting a triggering
operation on the application platform; obtain historical operation information of
the electronic device in a preset period prior to the triggering time point; and input
the historical operation information into a prediction model, the prediction model
for predicting the triggering probability values of the plurality of applications
in the application platform based on the historical operation information.
[0023] During inputting the historical operation information into the prediction model,
the processor is also configured to: classify the historical operation information
to obtain first-type information belonging to user interaction information and second-type
information belonging to system information of the electronic device; increase a weight
of the first-type information and decrease a weight of the second-type information;
and input the first-type information with the increased weight and the second-type
information with the decreased weight into the prediction model.
[0024] During downloading the resource files of the target application, the processor is
also configured to: obtain a data amount of resource files that need to be downloaded
for the target application; determine whether a triggering probability value of the
target application is greater than a second preset probability value under a case
that the data amount is greater than a preset data amount, the second preset probability
value being greater than the first preset probability value; download all the resource
files of the target application under a case that the triggering probability value
of the target application is greater than the second preset probability value; and
download part of the resource files of the target application under a case that the
triggering probability value of the target application is not greater than the second
preset probability value.
[0025] During downloading the resource files of the target application, the processor is
also configured to: obtain a pre-storage capacity corresponding to the target application
based on the triggering probability value of the target application; obtain a data
amount of resource files that need to be downloaded for the target application; detect
whether the storage area has a residual capacity under a case that the data amount
exceeds the pre-storage capacity; determine whether the data amount exceeds a sum
of the pre-storage capacity and the residual capacity under a case that there is the
residual capacity; and download the resource files of the target application under
a case that the data amount does not exceed the sum of the pre-storage capacity and
the residual capacity.
[0026] The processor is also configured to: select an application with a triggering probability
value not greater than the first preset probability value but greater than a third
preset probability value as an alternative application, in which the third preset
probability value is smaller than the first preset probability value; add an execution
entrance of the target application to a first preset position of a main interface
of the application platform; and add an execution entrance of the alternative application
to a second preset position of the main interface of the application platform.
[0027] The method for application processing is provided in embodiments of the disclosure.
An executing body of the method for application processing may be an apparatus for
application processing according to embodiments of the disclosure, or an electronic
device integrated with the apparatus for application processing. The apparatus for
application processing may be implemented in form of hardware or software. The electronic
device may be a smart phone, a tablet, a palm computer, a notebook computer, a desktop
computer, or other device.
[0028] Referring to FIG. 1, FIG. 1 is a schematic diagram illustrating a scenario of a method
for application processing according to embodiments of the disclosure. As illustrated
in FIG. 1, an electronic device 10 is coupled with an application server 30 through
a network 20.
[0029] The electronic device may be installed with an operating system suitable for hardware
of the electronic device based on an actual requirement, such as an android system,
an apple system, a windows system and a symbian system.
[0030] The network may be a wireless network or a wired network, which may include a network
entity such as a router and a gateway, and not be illustrated in FIG. 1. When the
network is the wireless network, the network may include one or a combination of a
wireless wide area network, a wireless local area network, a wireless metropolitan
area network, and a wireless personal network.
[0031] The application server stores a configuration file corresponding to an application.
When the configuration file is executed by the electronic device, a native interface
of the application is generated, that is, a same operation effect for installing a
related application is implemented under a premise that the related application is
not installed. It should be noted that, in addition to generating the configuration
file of the native interface, data required for operating the application may be obtained
from the application server in real time. Therefore, the native interface generated
by the electronic device executing the configuration file may be popularly called
as a "fast application". In addition, the application server, as a "middleman" between
a user and a developer of the application, provides an application platform service
for the user and the developer. On the one hand, the developer may upload the "fast
application" (including the configuration file and other files required for operating
the application) developed by the developer to the application server, and provide
the "fast application" to the user through the application server. On the other hand,
the user may query a "fast application" to be used through the application server
based on a requirement of the user, and use the "fast application" quickly.
[0032] Referring to FIG. 2, FIG. 2 is a flow chart illustrating a method for application
processing according to embodiments of the disclosure. A detailed procedure for the
method for application processing according to embodiments of the disclosure may include
the following.
[0033] At block 201, historical operation information of the electronic device is obtained,
and triggering probability values of a plurality of applications in an application
platform installed in the electronic device are obtained based on the historical operation
information.
[0034] The historical operation information of the electronic device may include a chat
record, input information, network browsing information, etc. of the user, and may
also include a system time, a remaining power, a current network state (e.g., a WIFI
state or a mobile network state), a network quality, an operation duration after the
electronic device is powered on, a latest screen rest time, a background application,
etc.
[0035] The application platform refers to a platform that aggregates execution entrances
of a plurality of fast applications in the electronic device, and the execution entrances
of different fast applications may be clicked on the application platform, thereby
entering a native page of the corresponding fast application. The fast application
does not need to be installed, but is operating through the application platform.
[0036] The triggering probability values of the plurality of applications in the application
platform are obtained based on the historical operation information.
[0037] In an implementation, obtaining the historical operation information of the electronic
device, and obtaining the triggering probability values of the plurality of applications
in the application platform based on the historical operation information include:
obtaining a triggering time point in response to detecting a triggering operation
on the application platform; obtaining historical operation information of the electronic
device in a preset period prior to the triggering time point; and inputting the historical
operation information into a prediction model, the prediction model for predicting
the triggering probability values of the plurality of applications in the application
platform based on the historical operation information.
[0038] Firstly, a reference time point is obtained, such as the triggering time point at
which the application platform is triggered. Then, the historical operation information
of the electronic device in the preset period prior to the triggering time point is
obtained. The triggering probability value of the application may be predicted more
accurately based on the historical operation information in the preset period. Finally,
the historical operation information in the preset period is inputted into the prediction
model. The prediction model performs prediction, to obtain the triggering probability
values of the plurality of applications in the application platform.
[0039] The prediction model may be a convolution neural network model, a circulation neural
network model, or the like. The more comprehensive and accurate input data, the more
accurate a later prediction result may be.
[0040] In an implementation, inputting the historical operation information into the prediction
model includes: classifying the historical operation information to obtain first-type
information belonging to user interaction information and second-type information
belonging to system information of the electronic device; increasing a weight of the
first-type information and decreasing a weight of the second-type information; and
inputting the first-type information with the increased weight and the second-type
information with the decreased weight into the prediction model.
[0041] Before the historical operation information is inputted into the prediction model,
the historical operation information is classified firstly, and the historical operation
information may be classified into the first-type information belonging to the user
interaction information and the second-type information belonging to the system information
of the electronic device. The first-type information may include chat record information,
user input information, user browsing webpage information, etc. The first-type information
is strongly related to the user, and the weight of the first-type information may
be correspondingly increased, to improve an impact on the prediction result. The second-type
information may include a system time, a current network state, a network quality,
and an operation time of the electronic device after powered on. A correlation between
the second-type information and the user is low, and the weight of the second-type
information may be decreased, to reduce the impact on the prediction result. The historical
operation information is classified, and the weights of different types of information
are adjusted, to improve the accuracy of the prediction result.
[0042] At block 202, an application with a triggering probability value greater than a first
preset probability value is selected as a target application.
[0043] A fixed first preset probability value, such as 0.6, may be preset. After the triggering
probability values of the plurality of applications are obtained, the triggering probability
value of each application is compared with the first preset probability value. When
the triggering probability value is greater than the first preset probability value,
the application is selected as the target application. Referring to FIG. 3, the application
platform includes an application A, an application B, an application C and an application
D. The application A and the application B with the triggering probability value greater
than the first preset probability value are selected as the target applications.
[0044] The first preset probability value may also be a floating probability value. For
example, when the triggering probability values of the plurality of applications are
sorted based on sizes of the triggering probability values, and there is a need to
select five applications as the target applications, the sixth triggering probability
value is selected as the first preset probability value, thereby obtaining the five
applications with the larger triggering probability values as the target applications.
[0045] In an implementation, the method also includes: selecting an application with a triggering
probability value not greater than the first preset probability value but greater
than a third preset probability value as an alternative application, in which, the
third preset probability value is smaller than the first preset probability value;
adding an execution entrance of the target application to a first preset position
of a main interface of the application platform; and adding an execution entrance
of the alternative application to a second preset position of the main interface of
the application platform.
[0046] There are a plurality of target applications and a plurality of alternative applications.
The execution entrances of the plurality of applications are displayed in the application
platform. The target application with the triggering probability value larger than
the first preset probability value is displayed at the first preset position, and
the alternative application with the smaller triggering probability value is displayed
at the second preset position. The first preset position is a more prominent position,
and the second preset position is a less prominent position. When the first preset
position is the middle, the second preset position is the periphery. The second preset
position may surround the first preset position. When the target application and the
alternative application are displayed in an arrangement, the target application is
displayed in the front, and the alternative application is displayed in the back.
Referring to FIG. 4, the application platform includes an application A, an application
B, an application C, an application D, an application E and an application F. A target
application A, a target application B, an alternative application E and an alternative
application F are obtained based on the triggering probability values, and arranged
based on the triggering probability values.
[0047] In addition, the execution entrance of the target application may be added with other
marker, such as added with a background color of other color, an underline, etc.
[0048] At block 203, resource files of the target application are downloaded, and the resource
files are buffered into a storage area corresponding to the application platform.
[0049] The resource files may include a configuration file of the target application or
the like.
[0050] The configuration file corresponding to the target application is a configuration
file of a fast application corresponding to the target application. The configuration
file is configured for the electronic device to generate and to display the native
interface of the target application, such that the electronic device may implement
a same operation effect of the installed target application without installing the
target application.
[0051] In detail, the configuration file includes statements describing the native interface
of the target application, and the statements include data required for displaying
the native interface and an operation logic of the native interface.
[0052] The data required for displaying the native interface may include display elements
that the target application interface needs to display, layout information of the
display elements, a resource address required for displaying each display element,
and the like. The layout information may include information such as a position, a
size, a color, etc. of each display element. The resource address may be an address
of a local resource of the electronic device or a link address of a resource stored
on the application server.
[0053] The operation logic of the native interface may include an interface address that
needs to be jumped when the display element is clicked, an operation that needs to
be executed when the display element is clicked, or operation that needs to be executed
and corresponds to the operation of other user.
[0054] The resource files may also include a file of a subdirectory in the application,
such as movie header image data of a certain movie in a video application.
[0055] After the target application is obtained, the resource files of each target application
may be downloaded. The resource files may be buffered into the storage area corresponding
to the application platform. The storage area corresponding to the application platform
may be a storage area designated by the electronic device for the application platform.
[0056] According to the invention, downloading the resource files of the target application
includes: obtaining a data amount of resource files that need to be downloaded for
the target application; determining whether a triggering probability value of the
target application is greater than a second preset probability value under a case
that the data amount is greater than a preset data amount, the second preset probability
value being greater than the first preset probability value; downloading all the resource
files of the target application under a case that the triggering probability value
of the target application is greater than the second preset probability value; and
downloading part of the resource files of the target application under a case that
the triggering probability value of the target application is not greater than the
second preset probability value.
[0057] The application platform sets a preset data amount corresponding to the target application
in advance. Before the resource files of the target application are downloaded, the
data amount of the resource files that need to be downloaded for the target application
are obtained firstly. And then it is determined whether the data amount is greater
than the preset data amount. When the data amount is less than or equal to the preset
data amount, the resource files of the target application are directly downloaded.
When the data amount is greater than the preset data amount, the resource files that
need to be downloaded are larger, which may affect a downloading rate and operation
efficiency of the electronic device, as well as a downloading rate of other target
application. In this case, it is also determined whether the triggering probability
value of the target application is greater than the second preset probability value.
The second preset probability value is greater than the first preset probability value.
For example, the first preset probability value is 0.6, and the second preset probability
value is 0.8. When the triggering probability value of the target application is greater
than the second preset probability value, there is a large possibility for triggering
the target application, and there is also a large possibility for subsequently downloading
the resource files. Therefore, the resource files may be downloaded currently. When
the triggering probability value of the target application is not greater than the
second preset probability value, a downloading amount of the target application is
limited, and the part of the resource files of the target application are merely downloaded,
thereby reducing a storage space, and reducing the effect on other target application.
[0058] In an implementation, the method further includes: adding an execution entrance of
the target application to a main interface of the electronic device under the case
that the triggering probability value of the target application is greater than the
second preset probability value.
[0059] When the triggering probability value of the target application is greater than the
second preset probability value, there is a large possibility for triggering the target
application. Therefore, the execution entrance of the target application is added
to the main interface of the electronic device, such that the user may enter the target
application quickly. The execution entrance may be displayed as a triggering icon.
When the triggering icon is clicked, the target application loads the resource files
for a normal use of the user.
[0060] According to the invention, downloading the resource files of the target application
also includes:
obtaining a pre-storage capacity corresponding to the target application based on
the triggering probability value of the target application; obtaining a data amount
of resource files that need to be downloaded for the target application; detecting
whether the storage area has a residual capacity under a case that the data amount
exceeds the pre-storage capacity; determining whether the data amount exceeds a sum
of the pre-storage capacity and the residual capacity under a case that there is the
residual capacity; and downloading the resource files of the target application under
a case that the data amount does not exceed the sum of the pre-storage capacity and
the residual capacity.
[0061] The storage space of the target application may be pre-allocated. For example, when
five target applications are set, and the storage space is 1M, the storage space (i.e.,
1M) may be allocated equally for the target applications may, and may also be allocated
based on a decreasing order of the triggering probability values. The pre-storage
capacity corresponding to the target application, and the data amount of the resource
files that need to be downloaded for the target application are obtained. Then, the
pre-storage capacity is compared with the data amount. When the data amount does not
exceed the pre-storage capacity, the resource files are downloaded directly. When
the data amount exceeds the pre-storage capacity, it is detected whether the storage
area has the residual capacity. When the storage area has the residual capacity, it
is determined whether the data amount exceeds the sum of the pre-storage capacity
and the residual capacity. When the data amount does not exceed the sum of the pre-storage
capacity and the residual capacity, the resource files of the target application are
downloaded.
[0062] When the storage area does not have the residual capacity, the part of the resource
files is downloaded. When the data amount exceeds the sum of the pre-storage capacity
and the residual capacity, the part of the resource files is downloaded.
[0063] The target application with a larger triggering probability value may be downloaded
preferentially. When the data amounts of two target applications exceed the pre-storage
capacity, the target application with the larger triggering probability value may
be preferentially satisfied.
[0064] At block 204, the resource files stored in the storage area and corresponding to
the target application are loaded in response to detecting a triggering operation
on the target application.
[0065] When the triggering operation on the target application is detected, there is no
need to download the resource files of the target application in large quantities
from the network, and the resource files are directly loaded from the storage area,
such that the configuration may be completed quickly, and launching the target application
may be accelerated. Referring to FIG. 5, a target application B is triggered by the
user, and the resource files of the target application B stored in the storage area
are loaded.
[0066] In an implementation, after the resource files of the target application are downloaded,
and the resource files are buffered into the storage area corresponding to the application
platform, the method further includes: obtaining a new triggering probability value
of the target application under a case that the storage area is full; and deleting
the resource files of the target application under a case that the new triggering
probability value is smaller than the first preset probability value.
[0067] When the storage area is full, the new triggering probability value of the target
application is reacquired, which starts from the target application with a smaller
triggering probability value. When the new triggering probability value of the target
application is smaller than the first preset probability value, the resource files
buffered by the target application are deleted, thereby saving the storage space.
[0068] When the storage area is full, the new triggering probability values of all the applications
in the application platform may also be reacquired, and a batch of target applications
are reacquired. When the target application obtained before is not the reacquired
target application, the resource files corresponding to the target application obtained
before are deleted, a new target application is added, and the resource files of the
reacquired target application are downloaded. When both the target application obtained
before and the target application obtained currently are the same target application,
it is determined whether the resource files of the target application are expired
or invalid. When the resource files are expired or invalid, the resource files are
downloaded again.
[0069] Referring to FIG. 6, FIG. 6 is another flow chart illustrating a method for application
processing according to embodiments of the disclosure. A detailed procedure of the
method for application processing according to this embodiment of the disclosure may
include the following.
[0070] At block 301, a triggering time point is obtained in response to detecting a triggering
operation on the application platform.
[0071] A reference time point is obtained firstly, such as the triggering time point at
which the application platform is triggered.
[0072] At block 302, historical operation information of the electronic device in a preset
period prior to the triggering time point is obtained.
[0073] Then, the historical operation information in the preset period prior to the triggering
time point is obtained. The triggering probability value of the application may be
predicted more accurately based on the historical operation information in the preset
period. The historical operation information of the electronic device may include
chat record, input information, network browsing information, etc. of the user, and
may also include a system time, a remaining power, a current network state (e.g.,
a WIFI state or a mobile network state), a network quality, an operation duration
after the electronic device is powered on, a latest screen rest time, a background
application, etc.
[0074] At block 303, the historical operation information is input into a prediction model,
and the prediction model is configured to predict triggering probability values of
a plurality of applications in the application platform based on the historical operation
information.
[0075] Then, the historical operation information in the preset period prior to the triggering
time point is obtained. The triggering probability value of the application may be
predicted more accurately based on the historical operation information in the preset
period. Finally, the historical operation information in the preset period is input
into the prediction model. The prediction model performs prediction, to obtain the
triggering probability values of the plurality of applications.
[0076] The prediction model may be a convolutional neural network model and a recurrent
neural network model. The more comprehensive and accurate input data, the more accurate
a prediction result may be.
[0077] At block 304, an application with a triggering probability value greater than a first
preset probability value is selected as a target application.
[0078] A fixed first preset probability value, such as 0.6, may be preset. After the triggering
probability values of the plurality of applications are obtained, the triggering probability
value of each application is compared with the first preset probability value. When
the triggering probability value of the application is greater than the first preset
probability value, the application is selected as the target application.
[0079] The first preset probability value may also be a floating probability value. For
example, when the triggering probability values of the plurality of applications are
sorted based on sizes of the triggering probability values, and there is a need to
select five applications as the target applications, the sixth triggering probability
value is selected as the first preset probability value, thereby obtaining the five
applications with the larger triggering probability values as the target applications.
[0080] At block 305, a data amount of resource files that need to be downloaded for the
target application is obtained.
[0081] Before the resource files of the target application are downloaded, the data amount
of resource files that need to be downloaded for the target application is obtained
firstly.
[0082] At block 306, it is determined whether that the data amount is greater than the preset
data amount.
[0083] At block 307, it is determined whether a triggering probability value of the target
application is greater than a second preset probability value under a case that the
data amount is greater than a preset data amount, the second preset probability value
being greater than the first preset probability value.
[0084] The application platform sets a preset data amount in advance for the target application.
[0085] At block 308, all the resource files of the target application are downloaded under
a case that the triggering probability value of the target application is greater
than the second preset probability value, and the resource files are buffered in a
storage area corresponding to the application platform.
[0086] When the data amount is greater than the preset data amount, the resource files that
need to be downloaded are larger, which may affect a downloading rate and an operation
efficiency of the electronic device, as well as a downloading rate of other target
application. In this case, it is also determined whether the triggering probability
value of the target application is greater than the second preset probability value.
The second preset probability value is greater than the first preset probability value.
For example, the first preset probability value is 0.6, and the second preset probability
value is 0.8. When the triggering probability value of the target application is greater
than the second preset probability value, there is a large possibility for triggering
the target application, and there is also a large possibility for subsequently downloading
the resource files. Therefore, the resource files may be downloaded currently. When
the triggering probability value of the target application is not greater than the
second preset probability value, a downloading amount of the target application is
limited, and the part of the resource files of the target application are merely downloaded,
thereby reducing a storage space, and reducing the effect on other target application.
[0087] At block 309, the part of the resource files of the target application are downloaded
under a case that the triggering probability value of the target application is not
greater than the second preset probability value.
[0088] When the data amount is lower than or equal to the preset data amount, the resource
files of the target application are downloaded directly.
[0089] At block 310, the resource files stored in the storage area and corresponding to
the target application are loaded in response to detecting a triggering operation
on the target application.
[0090] When the triggering operation on the target application is detected, there is no
need to download the resource files of the target application in large quantities
from the network, and the resource files are directly loaded from the storage area,
such that the configuration may be completed quickly, and launching the target application
may be accelerated.
[0091] At block 311, a new triggering probability value of the target application is obtained
under a case that the storage area is full.
[0092] When the storage area is full, the new triggering probability value of the target
application is reacquired, which may start from the target application with a smallest
triggering probability value. Or, when the storage area is full, new triggering probability
values of all the applications in the application platform may also be reacquired.
[0093] At block 312, the resource files of the target application are deleted under a case
that the new triggering probability value is smaller than the first preset probability
value.
[0094] When the new triggering probability value is reacquired from the target application
with the smallest triggering probability value, the resource files of the target application
are deleted under the case that the new triggering probability value is smaller than
the first preset probability value, thereby saving the storage space. Under the case
that the new triggering probability values of all the applications in the application
platform may be reacquired, and a batch of target applications are reacquired, when
the target application obtained before is not the target application obtained currently,
the resource files corresponding to the target application obtained before are deleted,
a new target application is added, and the resource files of the target application
obtained currently are downloaded. When both the target application obtained before
and the target application obtained currently are the same target application, it
is determined whether the resource files of the target application are expired or
invalid. When the resource files are expired or invalid, the resource files are downloaded
again.
[0095] It may be known above that, with this embodiment, the historical operation information
of the electronic device is obtained, and the triggering probability values of the
plurality of applications in the application platform are obtained based on the historical
operation information; the application with the triggering probability value greater
than the first preset probability value is set as the target application, to obtain
the at least one target application; the resource files of the target application
are downloaded, and the resource files are buffered into the storage area corresponding
to the application platform; and the resource files stored in the storage area and
corresponding to the target application are loaded in response to detecting the triggering
operation on the target application. The triggering probability value of the application
is predicted before the application is triggered. When the triggering probability
value of the application is greater than the first preset probability value, the resource
files are buffered. When the application is triggered, the buffered resource files
may be loaded, and there is no need to download the resource files temporarily, which
may improve a launching speed of the application.
[0096] In an embodiment, an apparatus for application processing may be also provided. Referring
to FIG. 7, FIG. 7 is a block diagram illustrating an apparatus for application processing
according to embodiments of the disclosure. The apparatus for application processing
400 is applied to an electronic device. The apparatus for application processing 400
includes a probability obtaining module 401, an application obtaining module 402,
a downloading module 403 and a loading module 404.
[0097] The probability obtaining module 401 is configured to: obtain historical operation
information of the electronic device, and obtain triggering probability values of
a plurality of applications in an application platform installed in the electronic
device based on the historical operation information.
[0098] The application obtaining module 402 is configured to select an application with
a triggering probability value greater than a first preset probability value as a
target application.
[0099] The downloading module 403 is configured to: download resource files of the target
application, and buffer the resource files into a storage area corresponding to the
application platform.
[0100] The loading module 404 is configured to: load the resource files stored in the storage
area and corresponding to the target application, in response to detecting a triggering
operation on the target application.
[0101] In an embodiment, referring to FIG. 8, FIG. 8 is another block diagram illustrating
an apparatus for application processing according to embodiments of the disclosure.
The probability obtaining module 401 includes a time point obtaining sub-module 4011,
an information obtaining sub-module 4012 and a probability obtaining sub-module 4013.
[0102] The time point obtaining sub-module 4011 is configured to obtain a triggering time
point in response to detecting a triggering operation on the application platform.
[0103] The information obtaining sub-module 4012 is configured to obtain historical operation
information of the electronic device in a preset period prior to the triggering time
point.
[0104] The probability obtaining sub-module 4013 is configured to input the historical operation
information into a prediction model, the prediction model for predicting the triggering
probability values of the plurality of applications in the application platform based
on the historical operation information.
[0105] In an embodiment, the probability obtaining module 401 is also configured to: classify
the historical operation information to obtain first-type information belonging to
user interaction information and second-type information belonging to system information
of the electronic device; increase a weight of the first-type information and decrease
a weight of the second-type information; and input the first-type information with
the increased weight and the second-type information with the decreased weight into
the prediction model.
[0106] In an embodiment, the downloading module 403 is also configured to: obtain a data
amount of resource files that need to be downloaded for the target application; determine
whether a triggering probability value of the target application is greater than a
second preset probability value under a case that the data amount is greater than
a preset data amount, the second preset probability value being greater than the first
preset probability value; download all the resource files of the target application
under a case that the triggering probability value of the target application is greater
than the second preset probability value; and download part of the resource files
of the target application under a case that the triggering probability value of the
target application is not greater than the second preset probability value.
[0107] In an embodiment, the apparatus also includes an adding module. The adding module
is configured to: add an execution entrance of the target application to a main interface
of the electronic device under the case that the triggering probability value of the
target application is greater than the second preset probability value.
[0108] In an embodiment, the downloading module 403 is also configured to: obtain a pre-storage
capacity corresponding to the target application based on the triggering probability
value of the target application; obtain a data amount of resource files that need
to be downloaded for the target application; detect whether the storage area has a
residual capacity under a case that the data amount exceeds the pre-storage capacity;
determine whether the data amount exceeds a sum of the pre-storage capacity and the
residual capacity under a case that there is the residual capacity; and download the
resource files of the target application under a case that the data amount does not
exceed the sum of the pre-storage capacity and the residual capacity.
[0109] In an embodiment, the application obtaining module 402 is also configured to: select
an application with a triggering probability value not greater than the first preset
probability value but greater than a third preset probability value as an alternative
application, in which the third preset probability value is smaller than the first
preset probability value; add an execution entrance of the target application to a
first preset position of a main interface of the application platform; and add an
execution entrance of the alternative application to a second preset position of the
main interface of the application platform.
[0110] In an embodiment, the apparatus also includes a deleting module. The deleting module
is configured to: obtain a new triggering probability value of the target application
under a case that the storage area is full; and delete the resource files of the target
application under a case that the new triggering probability value is smaller than
the first preset probability value.
[0111] It may be known above that, with this embodiment, the probability obtaining module
obtains the historical operation information of the electronic device, and obtains
the triggering probability values of the plurality of applications in the application
platform based on the historical operation information; the application obtaining
module sets the application with the triggering probability value greater than the
first preset probability value as the target application to obtain the at least one
target application; the downloading module downloads the resource files of the target
application, and buffers the resource files into the storage area corresponding to
the application platform; and the loading module loads the resource files stored in
the storage area and corresponding to the target application, in response to detecting
the triggering operation on the target application. The triggering probability value
of the application is predicted before the application is triggered. When the triggering
probability value of the application is greater than the first preset probability
value, the resource files are buffered. When the application is triggered, the buffered
resource files may be loaded, and there is no need to download the resource files
temporarily, which may improve a starting-up speed of the application.
[0112] Embodiments of the disclosure also provide an electronic device. Referring to FIG.
9, the electronic device 500 includes a processor 501 and a memory 502. The processor
501 is coupled to the memory 502 electrically.
[0113] The processor 500 is a control center of the electronic device 500. Various interfaces
and circuits are used to couple various parts of the entire electronic device. By
operating or loading a computer program stored in the memory 502 and calling data
stored in the memory 502, various functions of the electronic device 500 are executed
and data are processed, thereby implementing automatic change for material information
of the electronic device.
[0114] The memory 502 may be configured to store software programs and modules. The processor
501 is configured to execute various functional applications and data processing by
operating the computer programs and modules stored in the memory 502. The memory 502
may mainly include a storage program area and a storage data area. The storage program
area may store an operating system, computer programs required for at least one function
(such as a sound playing function, an image playing function, etc.) and the like.
The storage data area may store data or the like created based on the use of the electronic
device. In addition, the memory 502 may include a high-speed random-access memory,
and may also include a non-volatile memory, such as at least one of: a disk memory
device, a flash memory device, or other volatile solid-state memory device. Accordingly,
the memory 502 may also include a memory controller to provide access to the memory
502 by the processor 501.
[0115] In this embodiment of the disclosure, the processor 501 of the electronic device
500 may load instructions corresponding to processes of one or more computer programs
into the memory 502 based on the following actions, and the computer programs stored
in the memory 502 are executed by the processor 501, thereby implementing various
functions. The actions include: obtaining historical operation information of the
electronic device, and obtaining triggering probability values of a plurality of applications
in an application platform installed in the electronic device based on the historical
operation information; selecting an application with a triggering probability value
greater than a first preset probability value as a target application; downloading
resource files of the target application, and buffering the resource files into a
storage area corresponding to the application platform; and loading the resource files
stored in the storage area and corresponding to the target application, in response
to detecting a triggering operation on the target application.
[0116] In some implementation, during obtaining the historical operation information of
the electronic device, and obtaining the triggering probability values of the plurality
of applications in the application platform based on the historical operation information,
the processor 501 may be further configured to: obtain a triggering time point in
response to detecting a triggering operation on the application platform; obtain historical
operation information of the electronic device in a preset period prior to the triggering
time point; and input the historical operation information into a prediction model,
the prediction model for predicting the triggering probability values of the plurality
of applications in the application platform based on the historical operation information.
[0117] In some embodiments, during inputting the historical operation information into the
prediction model, the processor 501 may be also configured to: classify the historical
operation information to obtain first-type information belonging to user interaction
information and second-type information belonging to system information of the electronic
device; increase a weight of the first-type information and decrease a weight of the
second-type information; and input the first-type information with the increased weight
and the second-type information with the decreased weight into the prediction model.
[0118] In some embodiments, during downloading the resource files of the target application,
the processor 501 may be also configured to: obtain a data amount of resource files
that need to be downloaded for the target application; determine whether a triggering
probability value of the target application is greater than a second preset probability
value under a case that the data amount is greater than a preset data amount, the
second preset probability value being greater than the first preset probability value;
download all the resource files of the target application under a case that the triggering
probability value of the target application is greater than the second preset probability
value; and download part of the resource files of the target application under a case
that the triggering probability value of the target application is not greater than
the second preset probability value.
[0119] In some embodiments, the processor 501 may be configured to: add an execution entrance
of the target application to a main interface of the electronic device under the case
that the triggering probability value of the target application is greater than the
second preset probability value.
[0120] In some embodiments, during downloading the resource files of the target application,
the processor 501 may be configured to: obtain a pre-storage capacity corresponding
to the target application based on the triggering probability value of the target
application; obtain a data amount of resource files that need to be downloaded for
the target application; detect whether the storage area has a residual capacity under
a case that the data amount exceeds the pre-storage capacity; determine whether the
data amount exceeds a sum of the pre-storage capacity and the residual capacity under
a case that there is the residual capacity; and download the resource files of the
target application under a case that the data amount does not exceed the sum of the
pre-storage capacity and the residual capacity.
[0121] In some embodiments, the processor 501 may be configured to: select an application
with a triggering probability value not greater than the first preset probability
value but greater than a third preset probability value as an alternative application,
in which the third preset probability value is smaller than the first preset probability
value; add an execution entrance of the target application to a first preset position
of a main interface of the application platform; and add an execution entrance of
the alternative application to a second preset position of the main interface of the
application platform.
[0122] In some embodiments, the processor 501 may be configured to: obtain a new triggering
probability value of the target application under a case that the storage area is
full; and delete the resource files of the target application under a case that the
new triggering probability value is smaller than the first preset probability value.
[0123] It may be known above that, with this embodiment of the disclosure, the historical
operation information of the electronic device is obtained, and the triggering probability
values of the plurality of applications in the application platform are obtained based
on the historical operation information; the application with the triggering probability
value greater than the first preset probability value is set as the target application,
to obtain the at least one target application; the resource files of the target application
are downloaded, and the resource files are buffered into the storage area corresponding
to the application platform; and the resource files stored in the storage area and
corresponding to the target application are loaded in response to detecting the triggering
operation on the target application. The triggering probability value of the application
is predicted before the application is triggered. When the triggering probability
value of the application is greater than the first preset probability value, the resource
files are buffered. When the application is triggered, the buffered resource files
may be loaded, and there is no need to download the resource files temporarily, which
may improve a launching speed of the application.
[0124] Referring to FIG. 10, in some embodiments, the electronic device 500 may also include:
a display 503, a radio frequency circuit 504, an audio circuit 505, and a power supply
506. The display 503, the radio frequency circuit 504, the audio circuit 505, and
the power supply 506 are respectively coupled to the processor 501 electrically.
[0125] The display 503 may be configured to display information input by a user or information
provided to the user, and various graphical user interfaces. These graphical user
interfaces may include graphics, text, icons, videos, and any combination thereof.
The display 503 may include a display panel. In some embodiments, the display panel
may be configured in the form of a liquid crystal display (LCD), an organic light-emitting
diode (OLED), or the like.
[0126] The radio frequency circuit 504 may be configured to transmit and receive radio frequency
signals to establish a wireless communication with a network device or other electronic
device through the wireless communication, and to transmit and receive signals with
the network device or other electronic device.
[0127] The audio circuit 505 may be configured to provide an audio interface between the
user and the electronic device through a speaker and a microphone.
[0128] The power supply 506 may be configured to supply power to various components of the
electronic device 500. In some embodiments, the power supply 506 may be logically
coupled to the processor 501 through a power management system, thereby implementing
to manage charging, discharging, and power consumption management through the power
management system.
[0129] Although not illustrated in FIG. 10, the electronic device 500 may also include a
camera, a Bluetooth module, etc., which will not be described here.
[0130] Embodiments of the disclosure also provide a storage medium. The storage medium has
a computer program stored thereon. When the computer program is operating in an electronic
device, the electronic device is caused to execute the method for application processing
according to any one of the above embodiments. In this embodiment of the disclosure,
the storage medium may be a magnetic disk, an optical disk, a read only memory (ROM),
or a random-access memory (RAM), etc.
[0131] In the above embodiments, the description for each embodiment has its emphasis. For
parts not described in detail in one embodiment, please refer to the related description
for other embodiments.
[0132] It should be noted that, for the method for application processing according to embodiments
of the disclosure, ordinary testers in the art may understand that all or part of
the flows of the method for application processing according to embodiments of the
disclosure may be completed by the computer program controlling relevant hardware.
The computer program may be stored in a computer readable storage medium, such as
the memory of the electronic device, and executed by at least one processor in the
electronic device. The execution process may include, such as, a flow of any embodiment
of the method for application processing. The storage medium may be a magnetic disk,
an optical disk, a read-only memory, a random-access memory, etc.
[0133] For the apparatus for application processing according to embodiments of the disclosure,
respective functional modules may be integrated into one processing chip, or exist
separately physically, or two or more modules may be integrated into one module. The
above integrated modules may be implemented in the form of hardware or software functional
modules. If the integrated modules are implemented in the form of software functional
modules, and sold or used as an independent product, the integrated modules may also
be stored in the computer readable storage medium, such as read-only memory, magnetic
disk or optical disk.
[0134] The method and apparatus for application processing and, the storage medium and the
electronic device according to embodiments of the disclosure are described in detail
above. In the disclosure, detailed examples are applied to explain the principle and
the implementations of the disclosure. The description of the above embodiments is
only used to help understand the method and the core ideas of the disclosure.
1. A method for application processing executed by an apparatus, integrated with an electronic
device, and comprising:
obtaining (201) historical operation information of the electronic device;
obtaining (201) triggering probability values of a plurality of applications in an
application platform installed in the electronic device based on the historical operation
information;
selecting (202) an application with a triggering probability value greater than a
first preset probability value as a target application;
downloading (203) resource files of the target application;
buffering (203) the resource files into a storage area corresponding to the application
platform; and
loading (204) the resource files stored in the storage area and corresponding to the
target application, in response to detecting a triggering operation on the target
application,
being characterized in that:
downloading (203) the resource files of the target application comprises:
obtaining a pre-storage capacity corresponding to the target application based on
the triggering probability value of the target application;
obtaining a data amount of resource files that need to be downloaded for the target
application;
detecting whether the storage area has a residual capacity if the data amount exceeds
the pre-storage capacity;
determining whether the data amount exceeds a sum of the pre-storage capacity and
the residual capacity if there is the residual capacity;
downloading the resource files of the target application if the data amount does not
exceed the sum of the pre-storage capacity and the residual capacity; and
downloading part of the resource files of the target application if the data amount
exceeds the sum of the pre-storage capacity and the residual capacity,
downloading (203) the resource files of the target application also comprises:
obtaining (305) a data amount of resource files that need to be downloaded for the
target application;
determining (307) whether a triggering probability value of the target application
is greater than a second preset probability value if the data amount is greater than
a preset data amount, the second preset probability value being greater than the first
preset probability value;
downloading (308) all the resource files of the target application if the triggering
probability value of the target application is greater than the second preset probability
value; and
downloading (309) part of the resource files of the target application if the triggering
probability value of the target application is not greater than the second preset
probability value.
2. The method of claim 1, wherein obtaining (201) the historical operation information
of the electronic device, and obtaining (201) the triggering probability values of
the plurality of applications in the application platform installed in the electronic
device based on the historical operation information comprises:
obtaining (301) a triggering time point in response to detecting a triggering operation
on the application platform;
obtaining (302) historical operation information of the electronic device in a preset
period prior to the triggering time point; and
inputting (303) the historical operation information into a prediction model, the
prediction model for predicting the triggering probability values of the plurality
of applications in the application platform based on the historical operation information.
3. The method of claim 2, wherein inputting (303) the historical operation information
into the prediction model comprises:
classifying the historical operation information to obtain first-type information
belonging to user interaction information and second-type information belonging to
system information of the electronic device;
increasing a weight of the first-type information and decreasing a weight of the second-type
information; and
inputting the first-type information with the increased weight and the second-type
information with the decreased weight into the prediction model.
4. The method of claim 2 or 3, wherein the prediction model comprises at least one of:
a convolutional neural network model and a recurrent neural network model.
5. The method of claim 1, further comprising:
adding an execution entrance of the target application to a main interface of the
electronic device under the case that the triggering probability value of the target
application is greater than the second preset probability value.
6. The method of any one of claims 1 to 5, further comprising:
selecting an application with a triggering probability value not greater than the
first preset probability value but greater than a third preset probability value as
an alternative application, wherein the third preset probability value is smaller
than the first preset probability value;
adding an execution entrance of the target application to a first preset position
of a main interface of the application platform; and
adding an execution entrance of the alternative application to a second preset position
of the main interface of the application platform.
7. The method of claim 6, wherein there are a plurality of target applications and a
plurality of alternative applications, and the second preset position is set around
the first preset position.
8. The method of claim 6, wherein there are a plurality of target applications and a
plurality of alternative applications, and the plurality of target applications and
the plurality of alternative applications are displayed in an arrangement of the triggering
probability values.
9. The method of claim 6, further comprising:
obtaining (311) a new triggering probability value of the target application if the
storage area is full; and
deleting (312) the resource files of the target application if the new triggering
probability value is smaller than the first preset probability value.
10. The method of any one of claims 1 to 9, further comprising:
generating and displaying a native interface of the target application based on a
configuration file of the target application included in the resource files.
11. The method of claim 10, wherein the configuration file comprises statements describing
the native interface of the target application, and the statements comprise data required
for displaying the native interface and an operation logic of the native interface.
12. An apparatus (400) for application processing, integrated with an electronic device,
and comprising:
a probability obtaining module (401) configured to: obtain historical operation information
of the electronic device, and obtain triggering probability values of a plurality
of applications in an application platform installed in the electronic device based
on the historical operation information;
an application obtaining module (402) configured to select an application with a triggering
probability value greater than a first preset probability value as a target application;
a downloading module (403) configured to: download resource files of the target application,
and buffer the resource files into a storage area corresponding to the application
platform; and
a loading module (404) configured to: load the resource files stored in the storage
area and corresponding to the target application, in response to detecting a triggering
operation on the target application,
being characterized in that:
the downloading module (403) is configured to: obtain a pre-storage capacity corresponding
to the target application based on the triggering probability value of the target
application; obtain a data amount of resource files that need to be downloaded for
the target application; detect whether the storage area has a residual capacity if
the data amount exceeds the pre-storage capacity; determine whether the data amount
exceeds a sum of the pre-storage capacity and the residual capacity if there is the
residual capacity; and download the resource files of the target application if the
data amount does not exceed the sum of the pre-storage capacity and the residual capacity
and download part of the resource files of the target application if the data amount
exceeds the sum of the pre-storage capacity and the residual capacity,
the downloading module (403) is also configured to: obtain a data amount of resource
files that need to be downloaded for the target application; determine whether a triggering
probability value of the target application is greater than a second preset probability
value if the data amount is greater than a preset data amount, the second preset probability
value being greater than the first preset probability value; download all the resource
files of the target application if the triggering probability value of the target
application is greater than the second preset probability value; and download part
of the resource files of the target application if the triggering probability value
of the target application is not greater than the second preset probability value.
13. A storage medium having a computer program stored thereon, wherein an electronic device
is caused to execute the method for application processing method according to any
one of claims 1-11 when the computer program is executed by the electronic device.
1. Verarbeitungsverfahren für Anwendungen, das von einer Vorrichtung ausgeführt wird,
die in eine elektronische Vorrichtung integriert ist, und umfasst:
Erhalten (201) von historischen Betriebsinformationen der elektronischen Vorrichtung;
Erhalten (201) von Auslösewahrscheinlichkeitswerten einer Mehrzahl von Anwendungen
in einer in der elektronischen Vorrichtung installierten Anwendungsplattform basierend
auf den historischen Betriebsinformationen;
Auswählen (202) einer Anwendung mit einem Auslösewahrscheinlichkeitswert, der größer
als ein erster voreingestellter Wahrscheinlichkeitswert ist, als eine Zielanwendung;
Herunterladen (203) von Ressourcendateien der Zielanwendung;
Puffern (203) der Ressourcendateien in einen der Anwendungsplattform entsprechenden
Speicherbereich; und
Laden (204) der Ressourcendateien, die im Speicherbereich gespeichert sind und der
Zielanwendung entsprechen, als Reaktion auf das Erkennen einer Auslöseoperation an
der Zielanwendung,
dadurch gekennzeichnet, dass:
das Herunterladen (203) der Ressourcendateien der Zielanwendung umfasst:
Erhalten einer der Zielanwendung entsprechenden Vorspeicherkapazität basierend auf
dem Auslösewahrscheinlichkeitswert der Zielanwendung;
Erhalten der Datenmenge der Ressourcendateien, die für die Zielanwendung heruntergeladen
werden müssen;
Erkennen, ob der Speicherbereich eine Restkapazität hat, wenn die Datenmenge die Vorspeicherkapazität
überschreitet;
Bestimmen, ob die Datenmenge eine Summe aus der Vorspeicherkapazität und der Restkapazität
überschreitet, wenn die Restkapazität vorhanden ist;
Herunterladen der Ressourcendateien der Zielanwendung, wenn die Datenmenge die Summe
aus Vorspeicherkapazität und Restkapazität nicht überschreitet; und
Herunterladen eines Teils der Ressourcendateien der Zielanwendung, wenn die Datenmenge
die Summe aus Vorspeicherkapazität und Restkapazität überschreitet, das Herunterladen
(203) der Ressourcendateien der Zielanwendung ebenfalls umfasst:
Erhalten (305) einer Datenmenge von Ressourcendateien, die für die Zielanwendung heruntergeladen
werden müssen; Bestimmen (307), ob ein Auslösewahrscheinlichkeitswert der Zielanwendung
größer als ein zweiter voreingestellter Wahrscheinlichkeitswert ist, wenn die Datenmenge
größer als eine voreingestellte Datenmenge ist, wobei der zweite voreingestellte Wahrscheinlichkeitswert
größer als der erste voreingestellte Wahrscheinlichkeitswert ist;
Herunterladen (308) aller Ressourcendateien der Zielanwendung, wenn der Auslösewahrscheinlichkeitswert
der Zielanwendung größer als der zweite voreingestellte Wahrscheinlichkeitswert ist;
und
Herunterladen (309) eines Teils der Ressourcendateien der Zielanwendung, wenn der
Auslösewahrscheinlichkeitswert der Zielanwendung nicht größer als der zweite voreingestellte
Wahrscheinlichkeitswert ist.
2. Verfahren nach Anspruch 1, wobei das Erhalten (201) der historischen Betriebsinformationen
der elektronischen Vorrichtung und das Erhalten (201) der Auslösewahrscheinlichkeitswerte
der Mehrzahl von Anwendungen in der in der elektronischen Vorrichtung installierten
Anwendungsplattform basierend auf den historischen Betriebsinformationen umfasst:
Erhalten (301) eines Auslösezeitpunkts als Reaktion auf das Erkennen einer Auslöseoperation
auf der Anwendungsplattform;
Erhalten (302) von historischen Betriebsinformationen der elektronischen Vorrichtung
in einer voreingestellten Zeitspanne vor dem Auslösezeitpunkt; und
Eingeben (303) der historischen Betriebsinformationen in ein Vorhersagemodell, wobei
das Vorhersagemodell zum Vorhersagen der Auslösewahrscheinlichkeitswerte der Mehrzahl
von Anwendungen in der Anwendungsplattform basierend auf den historischen Betriebsinformationen
dient.
3. Verfahren nach Anspruch 2, wobei das Eingeben (303) der historischen Betriebsinformationen
in das Vorhersagemodell umfasst:
Klassifizieren der historischen Betriebsinformationen, um Informationen eines ersten
Typs zu erhalten, die zu Benutzerinteraktionsinformationen gehören, und
Informationen eines zweiten Typs, die zu Systeminformationen der elektronischen Vorrichtung
gehören;
Erhöhen einer Gewichtung der Informationen des ersten Typs und Verringern einer Gewichtung
der Informationen des zweiten Typs; und
Eingeben der Informationen des ersten Typs mit der erhöhten Gewichtung und der Informationen
des zweiten Typs mit der verringerten Gewichtung in das Vorhersagemodell.
4. Verfahren nach Anspruch 2 oder 3, wobei das Vorhersagemodell mindestens eines der
folgenden Modelle umfasst: ein Modell eines neuronalen Faltungsnetzwerks und ein Modell
eines rekurrenten neuronalen Netzwerks.
5. Verfahren nach Anspruch 1, ferner umfassend:
Hinzufügen einer Ausführungseingabe der Zielanwendung zu einer Hauptschnittstelle
der elektronischen Vorrichtung für den Fall, dass der Auslösewahrscheinlichkeitswert
der Zielanwendung größer ist als der zweite voreingestellte Wahrscheinlichkeitswert.
6. Verfahren nach einem der Ansprüche 1 bis 5, ferner umfassend:
Auswählen einer Anwendung mit einem Auslösewahrscheinlichkeitswert, der nicht größer
als der erste voreingestellte Wahrscheinlichkeitswert, aber größer als ein dritter
voreingestellter Wahrscheinlichkeitswert ist, als eine alternative Anwendung, wobei
der dritte voreingestellte Wahrscheinlichkeitswert kleiner als der erste voreingestellte
Wahrscheinlichkeitswert ist;
Hinzufügen einer Ausführungseingabe der Zielanwendung zu einer ersten voreingestellten
Position einer Hauptschnittstelle der Anwendungsplattform; und
Hinzufügen einer Ausführungseingabe der alternativen Anwendung zu einer zweiten voreingestellten
Position der Hauptschnittstelle der Anwendungsplattform.
7. Verfahren nach Anspruch 6, wobei eine Mehrzahl von Zielanwendungen und eine Mehrzahl
von alternativen Anwendungen vorhanden sind und die zweite voreingestellte Position
um die erste voreingestellte Position herum eingestellt ist.
8. Verfahren nach Anspruch 6, wobei eine Mehrzahl von Zielanwendungen und eine Mehrzahl
von alternativen Anwendungen vorhanden sind und die Mehrzahl von Zielanwendungen und
die Mehrzahl von alternativen Anwendungen in einer Anordnung der Auslösewahrscheinlichkeitswerte
angezeigt werden.
9. Verfahren nach Anspruch 6, ferner umfassend:
Erhalten (311) eines neuen Auslösewahrscheinlichkeitswerts der Zielanwendung, wenn
der Speicherbereich voll ist; und
Löschen (312) der Ressourcendateien der Zielanwendung, wenn der neue Auslösewahrscheinlichkeitswert
kleiner ist als der erste voreingestellte Wahrscheinlichkeitswert.
10. Verfahren nach einem der Ansprüche 1 bis 9, ferner umfassend:
Erzeugen und Anzeigen einer nativen Schnittstelle der Zielanwendung basierend auf
einer Konfigurationsdatei der Zielanwendung, die in den Ressourcendateien enthalten
ist.
11. Verfahren nach Anspruch 10, wobei die Konfigurationsdatei Aussagen umfasst, die die
native Schnittstelle der Zielanwendung beschreiben, und die Aussagen Daten umfassen,
die zum Anzeigen der nativen Schnittstelle und einer Betriebslogik der nativen Schnittstelle
erforderlich sind.
12. Verarbeitungsvorrichtung (400) für Anwendungen, die in eine elektronische Vorrichtung
integriert ist und umfasst:
ein Wahrscheinlichkeitserhaltungsmodul (401), das dazu ausgelegt ist: historische
Betriebsinformationen der elektronischen Vorrichtung zu erhalten, und Auslösewahrscheinlichkeitswerte
einer Mehrzahl von Anwendungen in einer in der elektronischen Vorrichtung installierten
Anwendungsplattform basierend auf den historischen Betriebsinformationen zu erhalten;
ein Anwendungserhaltungsmodul (402), das dazu ausgelegt ist, eine Anwendung mit einem
Auslösewahrscheinlichkeitswert, der größer als ein erster voreingestellter Wahrscheinlichkeitswert
ist, als eine Zielanwendung auszuwählen;
ein Herunterlademodul (403), das dazu ausgelegt ist:
Ressourcendateien der Zielanwendung herunterzuladen und die Ressourcendateien in einen
Speicherbereich zu puffern, der der Anwendungsplattform entspricht; und
ein Lademodul (404), das dazu ausgelegt ist: die im Speicherbereich gespeicherten
und der Zielanwendung entsprechenden Ressourcendateien zu laden, als Reaktion auf
das Erkennen einer Auslöseoperation bei der Zielanwendung,
die dadurch gekennzeichnet sind, dass:
das Herunterlademodul (403) dazu ausgelegt ist: eine der Zielanwendung entsprechende
Vorspeicherkapazität basierend auf dem Auslösewahrscheinlichkeitswert der Zielanwendung
zu erhalten; eine Datenmenge von Ressourcendateien zu erhalten, die für die Zielanwendung
heruntergeladen werden müssen; zu erkennen, ob der Speicherbereich eine Restkapazität
hat, wenn die Datenmenge die Vorspeicherkapazität überschreitet; zu bestimmen, ob
die Datenmenge eine Summe aus der Vorspeicherkapazität und der Restkapazität überschreitet,
wenn die Restkapazität vorhanden ist; und die Ressourcendateien der Zielanwendung
herunterzuladen, wenn die Datenmenge die Summe aus Vorspeicherkapazität und Restkapazität
nicht überschreitet, und einen Teil der Ressourcendateien der Zielanwendung herunterzuladen,
wenn die Datenmenge die Summe aus Vorspeicherkapazität und Restkapazität überschreitet,
das Herunterladenmodul (403) ebenfalls dazu ausgelegt ist: eine Datenmenge von Ressourcendateien
zu erhalten, die für die Zielanwendung heruntergeladen werden müssen; zu bestimmen,
ob ein Auslösewahrscheinlichkeitswert der Zielanwendung größer als ein zweiter voreingestellter
Wahrscheinlichkeitswert ist, wenn die Datenmenge größer als eine voreingestellte Datenmenge
ist, wobei der zweite voreingestellte Wahrscheinlichkeitswert größer als der erste
voreingestellte Wahrscheinlichkeitswert ist; alle Ressourcendateien der Zielanwendung
herunterzuladen, wenn der Auslösewahrscheinlichkeitswert der Zielanwendung größer
als der zweite voreingestellte Wahrscheinlichkeitswert ist; und einen Teil der Ressourcendateien
der Zielanwendung herunterzuladen, wenn der Auslösewahrscheinlichkeitswert der Zielanwendung
nicht größer als der zweite voreingestellte Wahrscheinlichkeitswert ist.
13. Speichermedium mit einem darauf gespeicherten Computerprogramm, wobei eine elektronische
Vorrichtung veranlasst wird, das Verarbeitungsverfahren für Anwendungen nach einem
der Ansprüche 1-11 auszuführen, wenn das Computerprogramm von der elektronischen Vorrichtung
ausgeführt wird.
1. Procédé de traitement d'application exécuté par un appareil, intégré avec un dispositif
électronique, et comprenant :
l'obtention (201) d'informations de fonctionnement historiques du dispositif électronique
;
l'obtention (201) de valeurs de probabilité de déclenchement d'une pluralité d'applications
dans une plate-forme d'application installée dans le dispositif électronique sur la
base des informations de fonctionnement historiques ;
la sélection (202) d'une application ayant une valeur de probabilité de déclenchement
supérieure à une première valeur de probabilité prédéfinie en tant qu'application
cible ;
le téléchargement (203) des fichiers ressources de l'application cible ;
la mise en mémoire tampon (203) des fichiers ressources dans une zone de stockage
correspondant à la plate-forme d'application ; et
le chargement (204) des fichiers ressources stockés dans la zone de stockage et correspondant
à l'application cible, en réponse à la détection d'un fonctionnement de déclenchement
sur l'application cible,
étant caractérisé en ce que :
le téléchargement (203) des fichiers ressources de l'application cible comprend :
l'obtention d'une capacité de pré-stockage correspondant à l'application cible sur
la base de la valeur de probabilité de déclenchement de l'application cible ;
l'obtention d'une quantité de données de fichiers ressources qui doivent être téléchargés
pour l'application cible ;
la détection pour savoir si la zone de stockage possède une capacité résiduelle si
la quantité de données dépasse la capacité de pré-stockage ;
la détermination pour savoir si la quantité de données dépasse une somme de la capacité
de pré-stockage et la capacité résiduelle s'il y a la capacité résiduelle ;
le téléchargement des fichiers ressources de l'application cible si la quantité de
données ne dépasse pas la somme de la capacité de pré-stockage et la capacité résiduelle
; et
le téléchargement d'une partie des fichiers ressources de l'application cible si la
quantité de données dépasse la somme de la capacité de pré-stockage et la capacité
résiduelle,
le téléchargement (203) des fichiers ressources de l'application cible comprend également
:
l'obtention (305) d'une quantité de données de fichiers ressources qui doivent être
téléchargés pour l'application cible ;
la détermination (307) pour savoir si une valeur de probabilité de déclenchement de
l'application cible est supérieure à une deuxième valeur de probabilité prédéfinie
si la quantité de données est supérieure à une quantité de données prédéfinie, la
deuxième valeur de probabilité prédéfinie étant supérieure à la première valeur de
probabilité prédéfinie ;
le téléchargement (308) de tous les fichiers ressources de l'application cible si
la valeur de probabilité de déclenchement de l'application cible est supérieure à
la deuxième valeur de probabilité prédéfinie ; et
le téléchargement (309) d'une partie des fichiers ressources de l'application cible
si la valeur de probabilité de déclenchement de l'application cible n'est pas supérieure
à la deuxième valeur de probabilité prédéfinie.
2. Procédé selon la revendication 1, l'obtention (201) des informations de fonctionnement
historiques du dispositif électronique, et l'obtention (201) des valeurs de probabilité
de déclenchement de la pluralité d'applications dans la plate-forme d'application
installée dans le dispositif électronique sur la base des informations de fonctionnement
historiques comprennent :
l'obtention (301) d'un point temporel de déclenchement en réponse à la détection d'un
fonctionnement de déclenchement sur la plate-forme d'application ;
l'obtention (302) d'informations de fonctionnement historiques du dispositif électronique
dans une période prédéfinie avant le point temporel de déclenchement ; et
l'entrée (303) des informations de fonctionnement historiques dans un modèle de prédiction,
le modèle de prédiction servant à prédire les valeurs de probabilité de déclenchement
de la pluralité d'applications dans la plate-forme d'application sur la base des informations
de fonctionnement historiques.
3. Procédé selon la revendication 2, l'entrée (303) des informations de fonctionnement
historiques dans le modèle de prédiction comprenant :
la classification des informations de fonctionnement historiques pour obtenir des
informations de premier type appartenant à des informations d'interaction d'utilisateur
et des informations de deuxième type appartenant à des informations système du dispositif
électronique ;
l'augmentation d'une pondération des informations de premier type et la diminution
d'une pondération des informations de deuxième type ; et
l'entrée des informations de premier type avec la pondération augmentée et des informations
de deuxième type avec la pondération diminuée dans le modèle de prédiction.
4. Procédé selon la revendication 2 ou 3, le modèle de prédiction comprenant au moins
un modèle parmi : un modèle de réseau neuronal convolutionnel et un modèle de réseau
neuronal récurrent.
5. Procédé selon la revendication 1, comprenant en outre :
l'ajout d'une entrée d'exécution de l'application cible à une interface principale
du dispositif électronique au cas où la valeur de probabilité de déclenchement de
l'application cible est supérieure à la deuxième valeur de probabilité prédéfinie.
6. Procédé selon l'une quelconque des revendications 1 à 5, comprenant en outre :
la sélection d'une application avec une valeur de probabilité de déclenchement qui
n'est pas supérieure à la première valeur de probabilité prédéfinie mais est supérieure
à une troisième valeur de probabilité prédéfinie en tant qu'application alternative,
la troisième valeur de probabilité prédéfinie étant inférieure à la première valeur
de probabilité prédéfinie ;
l'ajout d'une entrée d'exécution de l'application cible à une première position prédéfinie
d'une interface principale de la plate-forme d'application ; et
l'ajout d'une entrée d'exécution de l'application alternative à une deuxième position
prédéfinie de l'interface principale de la plate-forme d'application.
7. Procédé selon la revendication 6, où il existe une pluralité d'applications cibles
et une pluralité d'applications alternatives, et la deuxième position prédéfinie étant
définie autour de la première position prédéfinie.
8. Procédé selon la revendication 6, où il existe une pluralité d'applications cibles
et une pluralité d'applications alternatives, et la pluralité d'applications cibles
et la pluralité d'applications alternatives étant affichées dans un agencement des
valeurs de probabilité de déclenchement.
9. Procédé selon la revendication 6, comprenant en outre :
l'obtention (311) d'une nouvelle valeur de probabilité de déclenchement de l'application
cible si la zone de stockage est pleine ; et
l'effacement (312) des fichiers ressources de l'application cible si la nouvelle valeur
de probabilité de déclenchement est inférieure à la première valeur de probabilité
prédéfinie.
10. Procédé selon l'une quelconque des revendications 1 à 9, comprenant en outre :
la génération et l'affichage d'une interface native de l'application cible sur la
base d'un fichier de configuration de l'application cible inclus dans les fichiers
ressources.
11. Procédé selon la revendication 10, le fichier de configuration comprenant des déclarations
décrivant l'interface native de l'application cible, et les déclarations comprenant
des données requises pour afficher l'interface native et une logique de fonctionnement
de l'interface native.
12. Appareil (400) destiné à un traitement d'application, intégré avec un dispositif électronique,
et comprenant :
un module d'obtention de probabilité (401) configuré pour : obtenir des informations
de fonctionnement historiques du dispositif électronique, et obtenir des valeurs de
probabilité de déclenchement d'une pluralité d'applications dans une plate-forme d'application
installée dans le dispositif électronique sur la base des informations de fonctionnement
historiques ;
un module d'obtention d'application (402) configuré pour sélectionner une application
ayant une valeur de probabilité de déclenchement supérieure à une première valeur
de probabilité prédéfinie en tant qu'application cible ;
un module de téléchargement (403) configuré pour :
télécharger des fichiers ressources de l'application cible, et mettre en mémoire tampon
les fichiers ressources dans une zone de stockage correspondant à la plate-forme d'application
; et
un module de chargement (404) configuré pour : charger les fichiers ressources stockés
dans la zone de stockage et correspondant à l'application cible, en réponse à la détection
d'un fonctionnement de déclenchement sur l'application cible,
étant caractérisé en ce que :
le module de téléchargement (403) est configuré pour :
obtenir une capacité de pré-stockage correspondant à l'application cible sur la base
de la valeur de probabilité de déclenchement de l'application cible ;
obtenir une quantité de données de fichiers ressources qui doivent être téléchargés
pour l'application cible ;
détecter si la zone de stockage possède une capacité résiduelle si la quantité de
données dépasse la capacité de pré-stockage ; déterminer si la quantité de données
dépasse une somme de la capacité de pré-stockage et la capacité résiduelle s'il y
a la capacité résiduelle ; et télécharger les fichiers ressources de l'application
cible si la quantité de données ne dépasse pas la somme de la capacité de pré-stockage
et la capacité résiduelle, et télécharger une partie des fichiers ressources de l'application
cible si la quantité de données dépasse la somme de la capacité de pré-stockage et
la capacité résiduelle,
le module de téléchargement (403) étant configuré également pour : obtenir une quantité
de données de fichiers ressources qui doivent être téléchargés pour l'application
cible ; déterminer si une valeur de probabilité de déclenchement de l'application
cible est supérieure à une deuxième valeur de probabilité prédéfinie si la quantité
de données est supérieure à une quantité de données prédéfinie, la deuxième valeur
de probabilité prédéfinie étant supérieure à la première valeur de probabilité prédéfinie
; télécharger tous les fichiers ressources de l'application cible si la valeur de
probabilité de déclenchement de l'application cible est supérieure à la deuxième valeur
de probabilité prédéfinie ; et télécharger une partie des fichiers ressources de l'application
cible si la valeur de probabilité de déclenchement de l'application cible n'est pas
supérieure à la deuxième valeur de probabilité prédéfinie.
13. Support de stockage sur lequel un programme informatique est stocké, un dispositif
électronique étant amené à exécuter le procédé pour un procédé de traitement d'application
selon l'une quelconque des revendications 1 à 11 lorsque le programme informatique
est exécuté par le dispositif électronique.